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Markov $L_2$ inequality with the Gegenbauer weight (1702.05963v1)
Published 20 Feb 2017 in math.CA
Abstract: For the Gegenbauer weight function $w_{\lambda}(t)=(1-t2){\lambda-1/2}$, $\lambda>-1/2$, we denote by $\Vert\cdot\Vert_{w_{\lambda}}$ the associated $L_2$-norm, $$ \Vert f\Vert_{w_{\lambda}}:=\Big(\int_{-1}{1}w_{\lambda}(t)f2(t)\,dt\Big){1/2}. $$ We study the Markov inequality $$ \Vert p{\prime}\Vert_{w_{\lambda}}\leq c_{n}(\lambda)\,\Vert p\Vert_{w_{\lambda}},\qquad p\in \mathcal{P}n, $$ where $\mathcal{P}_n$ is the class of algebraic polynomials of degree not exceeding $n$. Upper and lower bounds for the best Markov constant $c{n}(\lambda)$ are obtained, which are valid for all $n\in \mathbb{N}$ and $\lambda>-\frac{1}{2}$.